Evidence map›Paper›PMID 37034125›Full record

ArticleTranslational and clinical pharmacology2023

Analysis of the distribution of trial sites in South Korea using social network analysis.

Ki Young Huh, Kyung-Sang Yu, Ildae Song

Abstract read
In one paragraph

Article in Translational and clinical pharmacology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Ki Young HuhDepartment of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul 03080, Korea.ORCID https://orcid.org/0000-0002-1872-9954
Kyung-Sang YuDepartment of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul 03080, Korea.ORCID https://orcid.org/0000-0003-0921-7225
Ildae SongDepartment of Pharmaceutical Science and Technology, Kyungsung University, Busan 48434, Korea.ORCID https://orcid.org/0000-0002-3904-4735

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Location of trial sites can be a potential source of study bias. Considering that clinical trials have been mostly conducted in urban areas, the distribution of trial sites need to be evaluated. We analyzed clinical trial approval data using social network analysis to quantitatively assess the site-by-site connections. The approval list of clinical trials from the Ministry of Food and Drug Safety database between 2014 and 2021 was analyzed. The number of clinical trials per trial site was counted according to the approval year and study phase and evaluated for distribution using empirical cumulative distribution function plots. Trial sites and conducts of a clinical trial were mapped into nodes and edges in the social network analysis, and basic network parameters were obtained. The clinical trials were concentrated at several trial sites. Forty-nine to 60.6% of phase 1 and up to 30% of the other study phases of clinical trials were at the top 5 trial sites. The annual distribution of the number of clinical trials per site was comparable across the study period. Connections among the trial sites in the metropolitan area were prominent. Graph size and density were higher in phase 3 trials than in the other phases. We demonstrated that the conduct of clinical trials was concentrated in the Seoul Metropolitan Area in both number of trials and connections using social network analysis.

Indexed as

Clinical TrialGeographySocial Network Analysis

Identifiers

PMID37034125
PMCPMC10079509

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.